Water Temperature Changes Related to Strong Earthquakes: The Case of the Jinjia Well, Southwest China

Round 1

Reviewer 1 Report

The work as a whole is of great interest for earthquake forecast, but there are some issues poorly described in the  manuscript:
1. Structure of the well:
1.1. According to fig. 2 shows that the well is piezometric. How deep is the water level?
1.2. What is the composition of the water?
1.3. How deep is the water level sensor?
1.4. Is the well equipped with protection against precipitation or water leakage with the earth surface?
1.5. Is the well in production? If yes, then provide a table with periods of pumping water.
2. Fig.8. In the time series of water level and temperature, seasonality is very well traced, therefore, in order to draw conclusions about anomalies in water temperature before earthquakes, this seasonality should be identified and removed from water temperature variations.

Author Response

Authors: Thank you for the comments.
1. Structure of the well:
1.1. According to fig. 2 shows that the well is piezometric. How deep is the water level?
1.2. What is the composition of the water?
1.3. How deep is the water level sensor?
1.4. Is the well equipped with protection against precipitation or water leakage with the earth surface?
1.5. Is the well in production? If yes, then provide a table with periods of pumping water.

 

Authors:

1.1. The water level is defined as the distance from the water surface to the well mouth. Fig.8. shows the range of water level is between 4.0 and 7.0 m from 2010 to 2015.

1.2. The aquifer is mainly composed of slate fissure water, with a chemical composition of HCO3-Ca·Na.

1.3. The water level sensor located at 10 m depth from the well mouth.

1.4. The borehole of the Jinjia well is sealed with casing pipe from surface, down to a depth of 95 m, in order to precipitation or water leakage with the earth surface.

1.5. The Jinjia Well is not in production. It has been a professional seismic observation well since the end of 1999.

We have modified Figure 2A, indicating the length of the casing pipe and filter pipe, and the placement of water level sensor. In section “2. Observational Background”, we added the statement “The aquifer is mainly composed of slate fissure water, with a chemical composition of HCO3-Ca·Na”.  In section 5.3, we added the following statement “Specifically, the water level was defined as the distance from the water surface to the well mouth. Figure 8B showed water level changes between 4.0 and 7.0 m from 2010 to 2015”.

2. 
   Fig.8. In the time series of water level and temperature, seasonality is very well traced, therefore, in order to draw conclusions about anomalies in water temperature before earthquakes, this seasonality should be identified and removed from water temperature variations.

Authors:

For the Jinjia well, the water level is indeed significantly affected by rainfall, but there is no significant seasonal variation in the water temperature from 2010 to 2015 (Figure 8), and there is also no significant seasonal variation in the water temperature from 2002 to 2009(Figure 3). Instead, the barometric pressure and monthly precipitation show periodic changes, but the water temperature was not affected by these variations.

Author Response File: Author Response.docx

Reviewer 2 Report

 

Dear authors,

I appreciate your efforts on this study and think you can fill in the gaps below for a possible publication in the journal.

Best regards.

Comments

1.      Studies of water temperatures and water level changes associated with strong earthquakes are very popular in the scientific community and there are many publications on this topic. In this study, geological data and well structure data were collected and water temperature gradients were measured in Jinjia well. The effectiveness of water temperature in predicting earthquakes was evaluated using the Molchan fault diagram method. Although the manuscript is well written, explained, and illustrated, it is an ordinary study on the Jinjia well in southwest China because you do not present any new information or approaches that will benefit the readers of the journal. It is therefore unclear what the main contribution to science is, apart from the characteristics of a case study in its present form.

2.      In its current state, it has a similarity rate of 24% according to the iThenticate report, which should be acceptable for several journals. However, 8% is from the Sun et al. (2018) paper, which should be reduced in the revision. In particular, check the lines between 218-237 in relation to Figure 6b, as this shows that you have not made much progress in this area by providing the same interpretation. Also, check if the official publication date of the above paper is 2017 or 2018.

3.      You should also address in the text the disadvantages of the Molchan fault diagram approach, if any.

4.      Please explain the other approaches used in earthquake prediction. Do you think that analysis of water temperature and changes in water level alone is sufficient for such an important issue? What do you think about integrating multiple approaches for this objective?

 

Author Response

Authors: Thank you for the comments.

 

Comments

1. Studies of water temperatures and water level changes associated with strong earthquakes are very popular in the scientific community and there are many publications on this topic. In this study, geological data and well structure data were collected and water temperature gradients were measured in Jinjia well. The effectiveness of water temperature in predicting earthquakes was evaluated using the Molchan fault diagram method. Although the manuscript is well written, explained, and illustrated, it is an ordinary study on the Jinjia well in southwest China because you do not present any new information or approaches that will benefit the readers of the journal. It is therefore unclear what the main contribution to science is, apart from the characteristics of a case study in its present form.

Authors:

We have stated in the beginning of the paper that the Jinjia well provides a continuous observation of the water temperature, and the Jinjia well is located in a place that moderate-strong earthquakes were frequently occurred. These are perfect conditions for a systematic study of the water temperature variation to earthquakes. Thus, it is useful to study the coseismic and preseismic changes and find the possible mechanism.

We added the statement in section “1. Introduction” and in section “6. Conclusion”, respectively. 

1. Introduction

Earthquake-induced or earthquake-related changes in temperature of groundwater contain rich information about the subsurface hydrogeological processes (Wang and Manga, 2021).

6. Conclusion

Our conclusion provides a good reference for the placement of water temperature probes, in order to better observe temperature changes related to earthquakes.

 

2. In its current state, it has a similarity rate of 24% according to the iThenticate report, which should be acceptable for several journals. However, 8% is from the Sun et al. (2018) paper, which should be reduced in the revision. In particular, check the lines between 218-237 in relation to Figure 6b, as this shows that you have not made much progress in this area by providing the same interpretation. Also, check if the official publication date of the above paper is 2017 or 2018.

Authors: We think it would be better to retain some explanations of the Molchan error diagram. Therefore, we made adjustments to some sentences between lines 218-237. The official publication date of the above paper is 2017, as shown in the following figure.

 

 

3. You should also address in the text the disadvantages of the Molchan fault diagram approach, if any.

Authors: The Molchan error diagram requires 2 or more earthquake cases to effectively test and predict.

4. Please explain the other approaches used in earthquake prediction. Do you think that analysis of water temperature and changes in water level alone is sufficient for such an important issue? What do you think about integrating multiple approaches for this objective?

Authors: Yes, multi-parametric monitoring is particularly important. We added the statement in the conclusion as follows: Our conclusion provides a good reference for the placement of water temperature probes, in order to better observe temperature changes related to earthquakes. Multi-parametric monitoring is particularly important both for identifying spurious anomalies and understanding the origin of hydrological changes. Combined water level, multi-depth water temperature, chemical composition of water (Skelton et al., 2014) and Stable isotopes (Hosono et al., 2020) would be more beneficial for studying groundwater flow and understanding the mechanisms related to earthquakes. 

Author Response File: Author Response.docx

Reviewer 3 Report

The manuscript titled " Water Temperature Changes Related to Strong Earthquakes: Case of the Jinjia Well, Southwest China " by Yang et al. analyzed the water temperature changes related to earthquakes. While the manuscript may be useful, the study looks immature in its present form. The authors should try to authenticate the results using more earthquakes. Here are some specific comments and suggestions:

1.     “The special tectonic location and placement of the temperature sensor were the reasons for the multiple abnormal changes in the water temperature related to earthquakes between 2002 and 2009 in the Jinjia well.” So this is the reason for abnormal water changes only for the specified period or the entire period?

2.     “The shorter the distance between the sensor and the fault, the higher the probability of water temperature changes related to earthquakes.” Try to state the reason for the statement.

3.     It is stated that the preseismic change of the Jinjia well is type ‘Λ’ (an initial increase followed by a subsequent decrease). Please elaborate if the same pattern is observed during all the earthquakes.

4.     The likely period of 125 days for any earthquake does not look relevant.

 

5.     Try to quote any other study after 2009.

Author Response

Authors: Thank you for the comments.

1. “The special tectonic location and placement of the temperature sensor were the reasons for the multiple abnormal changes in the water temperature related to earthquakes between 2002 and 2009 in the Jinjia well.” So this is the reason for abnormal water changes only for the specified period or the entire period?

Authors: The original description is not clear and we have revised the corresponding description in section “5.3. Mechanism of water temperature anomalies” as follows:

The Jinjia well and the earthquakes in this study are located in the stress-strain active region caused by the eastward movement of the Tibetan Plateau blocked by the South China Block. The borehole penetrates a fault at a depth of 109.2–115.7 m. This is the important tectonic and structural factor that water temperature of the Jinjia well can record changes related to earthquakes. The placement of temperature sensor is another important factor; According to our research results, if the temperature sensor was placed at a position of 135m or deeper between 2002 and 2009, the proportion of coseismic or preseismic abnormal changes recorded would be less. Therefore, the special tectonic location, well structure and placement of the temperature sensor were the reasons for the multiple abnormal changes in the water temperature related to earthquakes between 2002 and 2009 in the Jinjia well.

 

2. “The shorter the distance between the sensor and the fault, the higher the probability of water temperature changes related to earthquakes.” Try to state the reason for the statement.

Authors: We added the explaination in section “5.2. Influence of sensor location on water temperature” as follows: Fault zones are relatively weak locations. In the process of stress and strain accumula-tion in the source area, the regional tectonic stress changes. Non-seismogenic faults are prone to deformation, changes in pore pressure or permeability, leading to changes in fluid migration. However, in the case of long distances, the variation is relatively small and the range of influence is limited. The closer the temperature sensor in the wellbore is to the fault that undergoes subtle changes, the more likely it is to observe changes related to the earthquake preparation process. Therefore, the shorter the distance between the sensor and the fault, the higher the probability of water temperature changes related to earthquakes..

 

3. It is stated that the preseismic change of the Jinjia well is type ‘Λ’ (an initial increase followed by a subsequent decrease). Please elaborate if the same pattern is observed during all the earthquakes.

Authors: The symbol ‘Λ’ is not an accurate description of water temperature changes and we have corrected this description as follows: The preseismic abnormal changes of the Jinjia Well is rising-recovery (rising to a high value and continuing for a period of time before decreasing or quickly recovering).

 

4. The likely period of 125 days for any earthquake does not look relevant.

Authors: It indicates after the water temperature exceeds the threshold (16.9533 ℃)，the most likely time for an earthquake to occur is within the following 125 days. If the temperature continues to exceed the threshold, the sequence of time period during which earthquakes may occur will be delayed. The effective prediction time lasts until 125 days after the last temperature value above the threshold. The effective prediction time lasts until 125 days after the last temperature value above the threshold. Therefore, the four earthquakes Dayao M6.0 on July 21, 2003, Ninger M6.1 earthquake on June 3, 2007, Wenchuan M7.9 on May 12, 2008 and Panzhihua M6.0 earthquake on August 30, 2008 are considered to have been predicted correctly. Another correctly predicted earthquake is Dayao M6.1 on October 16, 2003.

Frankly, “125d” is not so clearly. In fact, we can obtain somewhat qualitative information. So, we revised the statement, namely “approximately 4 months”.

 

 

5. Try to quote any other study after 2009.

Authors: We read some literatures after 2009, added the following statemen in section “1. Introduction” and the literatures in the “References”.  

 

1. Introduction

Yan (2018) analyzed the coseismic and preseismic water temperature changes at Bang-lazhang hot spring in Longling county, Yunnan province, China. The numerical simula-tion results show that the decrease in the Balazhang spring water flow and temperature is attributed to the decrease in permeability caused by earthquakes（Yan et al. 2020). Water temperature usually show abnormal changes 1-6 months before strong earth-quakes in mainland China, e.g., the 2008 Wenchuan M7.9 (Yan et al. 2018), 2021 Yangbi M6.4 (Ma et al., 2021), 2022 Menyuan M6.9 (Zhong et al., 2022) earthquakes.

 

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Thank you

Reviewer 2 Report

Dear authors,

Thank you for considering the suggestions to improve the original version of the manuscript. It is now ripe for publication as a good case study on the subject.

Best regards.

Reviewer 3 Report

The authors have responded to my comments.